| Title | Big data analytics-artificial intelligence and sustainable performance through green supply chain practices in manufacturing firms of a developing country |
|---|---|
| ID_Doc | 19567 |
| Authors | Rashid, A; Baloch, N; Rasheed, R; Ngah, AH |
| Title | Big data analytics-artificial intelligence and sustainable performance through green supply chain practices in manufacturing firms of a developing country |
| Year | 2024 |
| Published | |
| Abstract | PurposeThis study aims to examine the role of big data analytics (BDA) powered by artificial intelligence (AI) in improving sustainable performance (SP) through green supply chain collaboration (GSCC), sustainable manufacturing (SM) and environmental process integration (EPI).Design/methodology/approachData was collected from 249 supply chain professionals working at various manufacturing firms, and hypotheses were tested through a quantitative method using PLS-SEM with the help of SmartPLS version 4 to validate the measurement model.FindingsThis study identified that BDA-AI significantly and positively affects GSCC, SM and EPI. Similarly, the results showed that GSCC significantly and positively affects SP. At the same time, SM and EPI have an insignificant effect on SP. The GSCC found a significant relationship between BDA-AI and SP for mediation. However, SM and environmental performance integration did not mediate the relationship between BDA and AI and SP.Originality/valueThis research evaluated a second-order model and tested SP in conjunction with the dynamic capability theory in the manufacturing industry of Pakistan. Therefore, this research could be beneficial for researchers, manufacturers and policymakers to attain sustainable goals by implementing the BDA-AI in the supply chain. |
Similar Articles
| ID | Score | Article |
|---|---|---|
18741
|
Gallo, H; Khadem, A; Alzubi, A The Relationship between Big Data Analytic-Artificial Intelligence and Environmental Performance: A Moderated Mediated Model of Green Supply Chain Collaboration (GSCC) and Top Management Commitment (TMC)(2023) | |
| 65562
|
Singh, SK; El-Kassar, AN Role of big data analytics in developing sustainable capabilities(2019) | |
| 31119
|
Waqas, M; Tan, LL Big data analytics capabilities for reinforcing green production and sustainable firm performance: the moderating role of corporate reputation and supply chain innovativeness(2023)Environmental Science And Pollution Research, 30, 6 | |
| 3868
|
Cheng, TCE; Kamble, SS; Belhadi, A; Ndubisi, NO; Lai, KH; Kharat, MG Linkages between big data analytics, circular economy, sustainable supply chain flexibility, and sustainable performance in manufacturing firms(2022)International Journal Of Production Research, 60, 22 | |
| 19144
|
Benzidia, S; Makaoui, N; Bentahar, O The impact of big data analytics and artificial intelligence on green supply chain process integration and hospital environmental performance(2021) | |
| 34492
|
Raut, RD; Mangla, SK; Narwane, VS; Gardas, BB; Priyadarshinee, P; Narkhede, BE Linking big data analytics and operational sustainability practices for sustainable business management(2019) | |
| 67325
|
AL-Khatib, AW; Shuhaiber, A Green Intellectual Capital and Green Supply Chain Performance: Does Big Data Analytics Capabilities Matter?(2022)Sustainability, 14, 16 | |
| 65766
|
Raut, RD; Mangla, SK; Narwane, VS; Dora, M; Liu, MQ Big Data Analytics as a mediator in Lean, Agile, Resilient, and Green (LARG) practices effects on sustainable supply chains(2021) | |
| 67204
|
Raj, R; Kumar, V; Verma, P Big data analytics in mitigating challenges of sustainable manufacturing supply chain(2023)Operations Management Research, 16, 4 | |
| 32601
|
Singh, RK; Joshi, HT Greening the supply chain: Institutional pressures, data-driven innovations, and the road to circular sustainability(2024) |